Overview

Dataset statistics

Number of variables11
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory97.3 B

Variable types

Text6
Categorical2
Numeric3

Alerts

홈페이지주소 has constant value ""Constant
소재지우편번호 is highly overall correlated with WGS84위도High correlation
WGS84위도 is highly overall correlated with 소재지우편번호High correlation
사찰명 has unique valuesUnique
사찰전화번호 has unique valuesUnique
소재지우편번호 has unique valuesUnique
소재지지번주소 has unique valuesUnique
소재지도로명주소 has unique valuesUnique
WGS84위도 has unique valuesUnique
WGS84경도 has unique valuesUnique

Reproduction

Analysis started2023-12-10 22:24:57.071819
Analysis finished2023-12-10 22:24:58.360049
Duration1.29 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Text

Distinct12
Distinct (%)57.1%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T07:24:58.438871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.1904762
Min length3

Characters and Unicode

Total characters67
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)23.8%

Sample

1st row가평군
2nd row가평군
3rd row고양시
4th row고양시
5th row과천시
ValueCountFrequency (%)
남양주시 4
19.0%
가평군 2
9.5%
고양시 2
9.5%
성남시 2
9.5%
수원시 2
9.5%
양주시 2
9.5%
용인시 2
9.5%
과천시 1
 
4.8%
광명시 1
 
4.8%
양평군 1
 
4.8%
Other values (2) 2
9.5%
2023-12-11T07:24:58.695090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 18
26.9%
양 9
13.4%
주 7
 
10.4%
남 6
 
9.0%
평 3
 
4.5%
군 3
 
4.5%
성 3
 
4.5%
원 2
 
3.0%
인 2
 
3.0%
용 2
 
3.0%
Other values (9) 12
17.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 18
26.9%
양 9
13.4%
주 7
 
10.4%
남 6
 
9.0%
평 3
 
4.5%
군 3
 
4.5%
성 3
 
4.5%
원 2
 
3.0%
인 2
 
3.0%
용 2
 
3.0%
Other values (9) 12
17.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 18
26.9%
양 9
13.4%
주 7
 
10.4%
남 6
 
9.0%
평 3
 
4.5%
군 3
 
4.5%
성 3
 
4.5%
원 2
 
3.0%
인 2
 
3.0%
용 2
 
3.0%
Other values (9) 12
17.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 18
26.9%
양 9
13.4%
주 7
 
10.4%
남 6
 
9.0%
평 3
 
4.5%
군 3
 
4.5%
성 3
 
4.5%
원 2
 
3.0%
인 2
 
3.0%
용 2
 
3.0%
Other values (9) 12
17.9%

사찰명
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T07:24:58.868386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0952381
Min length3

Characters and Unicode

Total characters65
Distinct characters36
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row백련사
2nd row대원사
3rd row중흥사
4th row흥국사
5th row연주암
ValueCountFrequency (%)
백련사 1
 
4.8%
정토사 1
 
4.8%
화운사 1
 
4.8%
법륜사 1
 
4.8%
신륵사 1
 
4.8%
용문사 1
 
4.8%
회암사 1
 
4.8%
육지장사 1
 
4.8%
수원사 1
 
4.8%
봉녕사 1
 
4.8%
Other values (11) 11
52.4%
2023-12-11T07:24:59.135835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 20
30.8%
봉 3
 
4.6%
용 2
 
3.1%
대 2
 
3.1%
원 2
 
3.1%
흥 2
 
3.1%
수 2
 
3.1%
주 2
 
3.1%
암 2
 
3.1%
정 2
 
3.1%
Other values (26) 26
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 65
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 20
30.8%
봉 3
 
4.6%
용 2
 
3.1%
대 2
 
3.1%
원 2
 
3.1%
흥 2
 
3.1%
수 2
 
3.1%
주 2
 
3.1%
암 2
 
3.1%
정 2
 
3.1%
Other values (26) 26
40.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 65
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 20
30.8%
봉 3
 
4.6%
용 2
 
3.1%
대 2
 
3.1%
원 2
 
3.1%
흥 2
 
3.1%
수 2
 
3.1%
주 2
 
3.1%
암 2
 
3.1%
정 2
 
3.1%
Other values (26) 26
40.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 65
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 20
30.8%
봉 3
 
4.6%
용 2
 
3.1%
대 2
 
3.1%
원 2
 
3.1%
흥 2
 
3.1%
수 2
 
3.1%
주 2
 
3.1%
암 2
 
3.1%
정 2
 
3.1%
Other values (26) 26
40.0%

사찰전화번호
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T07:24:59.304444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.809524
Min length11

Characters and Unicode

Total characters248
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row031-585-3853
2nd row031-582-0477
3rd row02-355-4488
4th row02-381-7980
5th row02-502-3234
ValueCountFrequency (%)
031-585-3853 1
 
4.8%
031-723-9797 1
 
4.8%
031-337-2576 1
 
4.8%
02-2031-2000 1
 
4.8%
031-885-9024 1
 
4.8%
031-775-5797 1
 
4.8%
031-866-0355 1
 
4.8%
031-871-0101 1
 
4.8%
031-245-9670 1
 
4.8%
031-256-4127 1
 
4.8%
Other values (11) 11
52.4%
2023-12-11T07:24:59.587005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 42
16.9%
0 36
14.5%
3 32
12.9%
1 26
10.5%
5 24
9.7%
7 21
8.5%
2 19
7.7%
8 16
 
6.5%
9 12
 
4.8%
6 12
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 206
83.1%
Dash Punctuation 42
 
16.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 36
17.5%
3 32
15.5%
1 26
12.6%
5 24
11.7%
7 21
10.2%
2 19
9.2%
8 16
7.8%
9 12
 
5.8%
6 12
 
5.8%
4 8
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 248
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 42
16.9%
0 36
14.5%
3 32
12.9%
1 26
10.5%
5 24
9.7%
7 21
8.5%
2 19
7.7%
8 16
 
6.5%
9 12
 
4.8%
6 12
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 248
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 42
16.9%
0 36
14.5%
3 32
12.9%
1 26
10.5%
5 24
9.7%
7 21
8.5%
2 19
7.7%
8 16
 
6.5%
9 12
 
4.8%
6 12
 
4.8%

홈페이지주소
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
https://www.templestay.com
21 

Length

Max length26
Median length26
Mean length26
Min length26

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowhttps://www.templestay.com
2nd rowhttps://www.templestay.com
3rd rowhttps://www.templestay.com
4th rowhttps://www.templestay.com
5th rowhttps://www.templestay.com

Common Values

ValueCountFrequency (%)
https://www.templestay.com 21
100.0%

Length

2023-12-11T07:24:59.700229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:24:59.780729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
https://www.templestay.com 21
100.0%

산명
Text

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T07:24:59.904522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.952381
Min length2

Characters and Unicode

Total characters62
Distinct characters37
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)90.5%

Sample

1st row축령산
2nd row명지산
3rd row북한산
4th row노고산
5th row관악산
ValueCountFrequency (%)
천마산 2
 
9.5%
축령산 1
 
4.8%
광교산 1
 
4.8%
멱조산 1
 
4.8%
문수산 1
 
4.8%
봉미산 1
 
4.8%
용문사 1
 
4.8%
천보산 1
 
4.8%
도리산 1
 
4.8%
팔달산 1
 
4.8%
Other values (10) 10
47.6%
2023-12-11T07:25:00.191937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 20
32.3%
천 3
 
4.8%
문 2
 
3.2%
마 2
 
3.2%
봉 2
 
3.2%
악 2
 
3.2%
멱 1
 
1.6%
수 1
 
1.6%
미 1
 
1.6%
사 1
 
1.6%
Other values (27) 27
43.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 62
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 20
32.3%
천 3
 
4.8%
문 2
 
3.2%
마 2
 
3.2%
봉 2
 
3.2%
악 2
 
3.2%
멱 1
 
1.6%
수 1
 
1.6%
미 1
 
1.6%
사 1
 
1.6%
Other values (27) 27
43.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 62
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 20
32.3%
천 3
 
4.8%
문 2
 
3.2%
마 2
 
3.2%
봉 2
 
3.2%
악 2
 
3.2%
멱 1
 
1.6%
수 1
 
1.6%
미 1
 
1.6%
사 1
 
1.6%
Other values (27) 27
43.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 62
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 20
32.3%
천 3
 
4.8%
문 2
 
3.2%
마 2
 
3.2%
봉 2
 
3.2%
악 2
 
3.2%
멱 1
 
1.6%
수 1
 
1.6%
미 1
 
1.6%
사 1
 
1.6%
Other values (27) 27
43.5%

프로그램유형
Categorical

Distinct3
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
당일형, 체험형, 휴식형
14 
체험형, 휴식형
5 
당일형
2 

Length

Max length13
Median length13
Mean length10.857143
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row체험형, 휴식형
2nd row체험형, 휴식형
3rd row당일형, 체험형, 휴식형
4th row당일형, 체험형, 휴식형
5th row당일형

Common Values

ValueCountFrequency (%)
당일형, 체험형, 휴식형 14
66.7%
체험형, 휴식형 5
 
23.8%
당일형 2
 
9.5%

Length

2023-12-11T07:25:00.295763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:25:00.385292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
체험형 19
35.2%
휴식형 19
35.2%
당일형 16
29.6%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13467.857
Minimum10580
Maximum18347
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T07:25:00.471338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10580
5-th percentile10582
Q112140
median12510
Q314332
95-th percentile17168
Maximum18347
Range7767
Interquartile range (IQR)2192

Descriptive statistics

Standard deviation2255.9525
Coefficient of variation (CV)0.16750642
Kurtosis-0.34010816
Mean13467.857
Median Absolute Deviation (MAD)1046
Skewness0.85211628
Sum282825
Variance5089321.7
MonotonicityNot monotonic
2023-12-11T07:25:00.566113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
12444 1
 
4.8%
12405 1
 
4.8%
18347 1
 
4.8%
16997 1
 
4.8%
17168 1
 
4.8%
12636 1
 
4.8%
12510 1
 
4.8%
11464 1
 
4.8%
11518 1
 
4.8%
16256 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
10580 1
4.8%
10582 1
4.8%
11464 1
4.8%
11518 1
4.8%
12001 1
4.8%
12140 1
4.8%
12141 1
4.8%
12202 1
4.8%
12405 1
4.8%
12444 1
4.8%
ValueCountFrequency (%)
18347 1
4.8%
17168 1
4.8%
16997 1
4.8%
16256 1
4.8%
16230 1
4.8%
14332 1
4.8%
13800 1
4.8%
13621 1
4.8%
13451 1
4.8%
12636 1
4.8%

소재지지번주소
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T07:25:00.753748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length23
Mean length20.761905
Min length15

Characters and Unicode

Total characters436
Distinct characters81
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row경기도 가평군 상면 연하리 366-5번지
2nd row경기도 가평군 북면 제령리 656-2번지
3rd row경기도 고양시 덕양구 북한동 259번지
4th row경기도 고양시 덕양구 지축동 203번지
5th row경기도 과천시 중앙동 85-1번지
ValueCountFrequency (%)
경기도 21
 
21.0%
남양주시 4
 
4.0%
가평군 2
 
2.0%
수원시 2
 
2.0%
성남시 2
 
2.0%
팔달구 2
 
2.0%
고양시 2
 
2.0%
덕양구 2
 
2.0%
처인구 2
 
2.0%
용인시 2
 
2.0%
Other values (58) 59
59.0%
2023-12-11T07:25:01.055554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
79
18.1%
기 22
 
5.0%
지 22
 
5.0%
경 21
 
4.8%
번 21
 
4.8%
도 21
 
4.8%
시 18
 
4.1%
2 15
 
3.4%
동 13
 
3.0%
3 12
 
2.8%
Other values (71) 192
44.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 281
64.4%
Space Separator 79
 
18.1%
Decimal Number 67
 
15.4%
Dash Punctuation 9
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 22
 
7.8%
지 22
 
7.8%
경 21
 
7.5%
번 21
 
7.5%
도 21
 
7.5%
시 18
 
6.4%
동 13
 
4.6%
양 11
 
3.9%
구 9
 
3.2%
리 8
 
2.8%
Other values (59) 115
40.9%
Decimal Number
ValueCountFrequency (%)
2 15
22.4%
3 12
17.9%
8 7
10.4%
1 7
10.4%
5 7
10.4%
4 6
 
9.0%
6 5
 
7.5%
9 4
 
6.0%
0 3
 
4.5%
7 1
 
1.5%
Space Separator
ValueCountFrequency (%)
79
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 281
64.4%
Common 155
35.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 22
 
7.8%
지 22
 
7.8%
경 21
 
7.5%
번 21
 
7.5%
도 21
 
7.5%
시 18
 
6.4%
동 13
 
4.6%
양 11
 
3.9%
구 9
 
3.2%
리 8
 
2.8%
Other values (59) 115
40.9%
Common
ValueCountFrequency (%)
79
51.0%
2 15
 
9.7%
3 12
 
7.7%
- 9
 
5.8%
8 7
 
4.5%
1 7
 
4.5%
5 7
 
4.5%
4 6
 
3.9%
6 5
 
3.2%
9 4
 
2.6%
Other values (2) 4
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 281
64.4%
ASCII 155
35.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
79
51.0%
2 15
 
9.7%
3 12
 
7.7%
- 9
 
5.8%
8 7
 
4.5%
1 7
 
4.5%
5 7
 
4.5%
4 6
 
3.9%
6 5
 
3.2%
9 4
 
2.6%
Other values (2) 4
 
2.6%
Hangul
ValueCountFrequency (%)
기 22
 
7.8%
지 22
 
7.8%
경 21
 
7.5%
번 21
 
7.5%
도 21
 
7.5%
시 18
 
6.4%
동 13
 
4.6%
양 11
 
3.9%
구 9
 
3.2%
리 8
 
2.8%
Other values (59) 115
40.9%

소재지도로명주소
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T07:25:01.255208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length20.333333
Min length14

Characters and Unicode

Total characters427
Distinct characters91
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row경기도 가평군 상면 샘골길 159-50
2nd row경기도 가평군 북면 백둔로 21-162
3rd row경기도 고양시 덕양구 대서문길 393
4th row경기도 고양시 덕양구 흥국사길 82
5th row경기도 과천시 자하동길 63
ValueCountFrequency (%)
경기도 21
 
21.0%
남양주시 4
 
4.0%
가평군 2
 
2.0%
수원시 2
 
2.0%
성남시 2
 
2.0%
팔달구 2
 
2.0%
고양시 2
 
2.0%
덕양구 2
 
2.0%
처인구 2
 
2.0%
용인시 2
 
2.0%
Other values (58) 59
59.0%
2023-12-11T07:25:01.557036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
79
 
18.5%
기 22
 
5.2%
경 21
 
4.9%
도 21
 
4.9%
1 19
 
4.4%
시 18
 
4.2%
로 14
 
3.3%
길 12
 
2.8%
3 11
 
2.6%
양 11
 
2.6%
Other values (81) 199
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 264
61.8%
Space Separator 79
 
18.5%
Decimal Number 79
 
18.5%
Dash Punctuation 5
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 22
 
8.3%
경 21
 
8.0%
도 21
 
8.0%
시 18
 
6.8%
로 14
 
5.3%
길 12
 
4.5%
양 11
 
4.2%
구 9
 
3.4%
주 8
 
3.0%
남 6
 
2.3%
Other values (69) 122
46.2%
Decimal Number
ValueCountFrequency (%)
1 19
24.1%
3 11
13.9%
2 10
12.7%
6 8
10.1%
5 8
10.1%
0 5
 
6.3%
4 5
 
6.3%
8 5
 
6.3%
7 4
 
5.1%
9 4
 
5.1%
Space Separator
ValueCountFrequency (%)
79
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 264
61.8%
Common 163
38.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 22
 
8.3%
경 21
 
8.0%
도 21
 
8.0%
시 18
 
6.8%
로 14
 
5.3%
길 12
 
4.5%
양 11
 
4.2%
구 9
 
3.4%
주 8
 
3.0%
남 6
 
2.3%
Other values (69) 122
46.2%
Common
ValueCountFrequency (%)
79
48.5%
1 19
 
11.7%
3 11
 
6.7%
2 10
 
6.1%
6 8
 
4.9%
5 8
 
4.9%
0 5
 
3.1%
- 5
 
3.1%
4 5
 
3.1%
8 5
 
3.1%
Other values (2) 8
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 264
61.8%
ASCII 163
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
79
48.5%
1 19
 
11.7%
3 11
 
6.7%
2 10
 
6.1%
6 8
 
4.9%
5 8
 
4.9%
0 5
 
3.1%
- 5
 
3.1%
4 5
 
3.1%
8 5
 
3.1%
Other values (2) 8
 
4.9%
Hangul
ValueCountFrequency (%)
기 22
 
8.3%
경 21
 
8.0%
도 21
 
8.0%
시 18
 
6.8%
로 14
 
5.3%
길 12
 
4.5%
양 11
 
4.2%
구 9
 
3.4%
주 8
 
3.0%
남 6
 
2.3%
Other values (69) 122
46.2%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.525562
Minimum37.169874
Maximum37.894327
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T07:25:01.664841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.169874
5-th percentile37.212171
Q137.297554
median37.550306
Q337.671566
95-th percentile37.850247
Maximum37.894327
Range0.72445272
Interquartile range (IQR)0.37401229

Descriptive statistics

Standard deviation0.2269474
Coefficient of variation (CV)0.0060478081
Kurtosis-1.3653655
Mean37.525562
Median Absolute Deviation (MAD)0.20367511
Skewness-0.012585892
Sum788.0368
Variance0.051505121
MonotonicityNot monotonic
2023-12-11T07:25:01.794049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
37.78420859 1
 
4.8%
37.89432675 1
 
4.8%
37.21217075 1
 
4.8%
37.2523066 1
 
4.8%
37.16987403 1
 
4.8%
37.29755376 1
 
4.8%
37.55030611 1
 
4.8%
37.85024673 1
 
4.8%
37.78407675 1
 
4.8%
37.28052265 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
37.16987403 1
4.8%
37.21217075 1
4.8%
37.2523066 1
4.8%
37.28052265 1
4.8%
37.29147841 1
4.8%
37.29755376 1
4.8%
37.346631 1
4.8%
37.426046 1
4.8%
37.44157036 1
4.8%
37.44180288 1
4.8%
ValueCountFrequency (%)
37.89432675 1
4.8%
37.85024673 1
4.8%
37.78420859 1
4.8%
37.78407675 1
4.8%
37.74709015 1
4.8%
37.67156605 1
4.8%
37.66366889 1
4.8%
37.66187504 1
4.8%
37.64604415 1
4.8%
37.62343117 1
4.8%

WGS84경도
Real number (ℝ)

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.16775
Minimum126.87296
Maximum127.66155
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T07:25:01.908929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.87296
5-th percentile126.93991
Q1127.00508
median127.12774
Q3127.26115
95-th percentile127.57117
Maximum127.66155
Range0.788589
Interquartile range (IQR)0.2560684

Descriptive statistics

Standard deviation0.21625026
Coefficient of variation (CV)0.0017005118
Kurtosis0.12053897
Mean127.16775
Median Absolute Deviation (MAD)0.13341
Skewness0.86611723
Sum2670.5227
Variance0.046764174
MonotonicityNot monotonic
2023-12-11T07:25:02.021681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
127.3498448 1
 
4.8%
127.5031456 1
 
4.8%
127.0050787 1
 
4.8%
127.1617147 1
 
4.8%
127.2986082 1
 
4.8%
127.6615526 1
 
4.8%
127.5711691 1
 
4.8%
127.1077686 1
 
4.8%
126.943966 1
 
4.8%
127.0187272 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
126.8729636 1
4.8%
126.939913 1
4.8%
126.943966 1
4.8%
126.9651412 1
4.8%
126.9761096 1
4.8%
127.0050787 1
4.8%
127.0187272 1
4.8%
127.0375411 1
4.8%
127.0678457 1
4.8%
127.1077686 1
4.8%
ValueCountFrequency (%)
127.6615526 1
4.8%
127.5711691 1
4.8%
127.5031456 1
4.8%
127.3498448 1
4.8%
127.2986082 1
4.8%
127.2611471 1
4.8%
127.2507832 1
4.8%
127.2181964 1
4.8%
127.183749 1
4.8%
127.1617147 1
4.8%

Interactions

2023-12-11T07:24:57.910892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:24:57.432965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:24:57.669328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:24:57.990085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:24:57.508533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:24:57.748832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:24:58.071574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:24:57.589699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:24:57.826349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:25:02.107143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명사찰명사찰전화번호산명프로그램유형소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
시군명1.0001.0001.0001.0000.8520.9961.0001.0000.7820.761
사찰명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
사찰전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
산명1.0001.0001.0001.0000.7361.0001.0001.0001.0001.000
프로그램유형0.8521.0001.0000.7361.0000.3291.0001.0000.0000.397
소재지우편번호0.9961.0001.0001.0000.3291.0001.0001.0000.5830.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
WGS84위도0.7821.0001.0001.0000.0000.5831.0001.0001.0000.678
WGS84경도0.7611.0001.0001.0000.3970.0001.0001.0000.6781.000
2023-12-11T07:25:02.210195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도프로그램유형
소재지우편번호1.000-0.8400.0270.214
WGS84위도-0.8401.0000.0970.000
WGS84경도0.0270.0971.0000.138
프로그램유형0.2140.0000.1381.000

Missing values

2023-12-11T07:24:58.187611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:24:58.308634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

시군명사찰명사찰전화번호홈페이지주소산명프로그램유형소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
0가평군백련사031-585-3853https://www.templestay.com축령산체험형, 휴식형12444경기도 가평군 상면 연하리 366-5번지경기도 가평군 상면 샘골길 159-5037.784209127.349845
1가평군대원사031-582-0477https://www.templestay.com명지산체험형, 휴식형12405경기도 가평군 북면 제령리 656-2번지경기도 가평군 북면 백둔로 21-16237.894327127.503146
2고양시중흥사02-355-4488https://www.templestay.com북한산당일형, 체험형, 휴식형10582경기도 고양시 덕양구 북한동 259번지경기도 고양시 덕양구 대서문길 39337.646044126.97611
3고양시흥국사02-381-7980https://www.templestay.com노고산당일형, 체험형, 휴식형10580경기도 고양시 덕양구 지축동 203번지경기도 고양시 덕양구 흥국사길 8237.663669126.939913
4과천시연주암02-502-3234https://www.templestay.com관악산당일형13800경기도 과천시 중앙동 85-1번지경기도 과천시 자하동길 6337.441803126.965141
5광명시금강정사02-899-7366https://www.templestay.com구름산당일형, 체험형, 휴식형14332경기도 광명시 소하동 340-1번지경기도 광명시 설월로 5837.44157126.872964
6남양주시묘적사031-577-1761https://www.templestay.com백봉산당일형, 체험형, 휴식형12202경기도 남양주시 와부읍 월문리 223번지경기도 남양주시 와부읍 수레로661번길 17437.623431127.261147
7남양주시봉선사031-527-9969https://www.templestay.com운악산당일형, 체험형, 휴식형12001경기도 남양주시 진접읍 부평리 255번지경기도 남양주시 진접읍 봉선사길 3237.74709127.183749
8남양주시봉인사031-528-5585https://www.templestay.com천마산체험형, 휴식형12140경기도 남양주시 진건읍 송능리 307번지경기도 남양주시 진건읍 사릉로156번길 29537.661875127.218196
9남양주시수진사031-591-3364https://www.templestay.com천마산당일형, 체험형, 휴식형12141경기도 남양주시 호평동 342-1번지경기도 남양주시 천마산로 115-1337.671566127.250783
시군명사찰명사찰전화번호홈페이지주소산명프로그램유형소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
11성남시정토사031-723-9797https://www.templestay.com청계산당일형, 체험형, 휴식형13451경기도 성남시 수정구 상적동 338번지경기도 성남시 수정구 옛골로42번길 337.426046127.067846
12수원시봉녕사031-256-4127https://www.templestay.com광교산당일형, 체험형, 휴식형16230경기도 수원시 팔달구 우만동 248번지경기도 수원시 팔달구 창룡대로 236-5437.291478127.037541
13수원시수원사031-245-9670https://www.templestay.com팔달산당일형16256경기도 수원시 팔달구 남수동 92-1번지경기도 수원시 팔달구 수원천로 30037.280523127.018727
14양주시육지장사031-871-0101https://www.templestay.com도리산체험형, 휴식형11518경기도 양주시 백석읍 기산리 294-3번지경기도 양주시 백석읍 기산로471번길 19037.784077126.943966
15양주시회암사031-866-0355https://www.templestay.com천보산당일형, 체험형, 휴식형11464경기도 양주시 회암동 4번지경기도 양주시 회암사길 28137.850247127.107769
16양평군용문사031-775-5797https://www.templestay.com용문사당일형, 체험형, 휴식형12510경기도 양평군 용문면 신점리 618번지경기도 양평군 용문면 용문산로 78237.550306127.571169
17여주시신륵사031-885-9024https://www.templestay.com봉미산당일형, 체험형, 휴식형12636경기도 여주시 천송동 282번지경기도 여주시 신륵사길 7337.297554127.661553
18용인시법륜사02-2031-2000https://www.templestay.com문수산당일형, 체험형, 휴식형17168경기도 용인시 처인구 원삼면 고당리 243-2번지경기도 용인시 처인구 원삼면 농촌파크로 12637.169874127.298608
19용인시화운사031-337-2576https://www.templestay.com멱조산당일형, 체험형, 휴식형16997경기도 용인시 처인구 삼가동 33-1번지경기도 용인시 처인구 동백죽전대로 111-1437.252307127.161715
20화성시용주사031-235-6886https://www.templestay.com화산체험형, 휴식형18347경기도 화성시 송산동 188번지경기도 화성시 용주로 13637.212171127.005079